Technological and methodological innovations are equipping researchers with unprecedented capabilities for detecting and characterizing pathologic processes in the developing human brain. As a result, ambitions to achieve clinically useful tools to assist in the diagnosis and management of mental health and learning disorders are gaining momentum. To this end, it is critical to accrue large-scale multimodal datasets that capture a broad range of commonly encountered clinical psychopathology. The Child Mind Institute has launched the Healthy Brain Network (HBN), an ongoing initiative focused on creating and sharing a biobank of data from 10,000 New York area participants (ages 5–21). The HBN Biobank houses data about psychiatric, behavioral, cognitive, and lifestyle phenotypes, as well as multimodal brain imaging (resting and naturalistic viewing fMRI, diffusion MRI, morphometric MRI), electroencephalography, eye-tracking, voice and video recordings, genetics and actigraphy. Here, we present the rationale, design and implementation of HBN protocols. We describe the first data release (n=664) and the potential of the biobank to advance related areas (e.g., biophysical modeling, voice analysis).

Technological and methodological innovations are equipping researchers with unprecedented capabilities for detecting and characterizing pathologic processes in the developing human brain. As a result, ambitions to achieve clinically useful tools to assist in the diagnosis and management of mental health and learning disorders are gaining momentum. To this end, it is critical to accrue large-scale multimodal datasets that capture a broad range of commonly encountered clinical psychopathology. The Child Mind Institute has launched the Healthy Brain Network (HBN), an ongoing initiative focused on creating and sharing a biobank of data from 10,000 New York area participants (ages 5-21). The HBN Biobank houses data about psychiatric, behavioral, cognitive, and lifestyle phenotypes, as well as multimodal brain imaging (resting and naturalistic viewing fMRI, diffusion MRI, morphometric MRI), electroencephalography, eye-tracking, voice and video recordings, genetics, and actigraphy. Here, we present the rationale, design and implementation of HBN protocols. We describe the first data release (n = 664) and the potential of the biobank to advance related areas (e.g., biophysical modeling, voice analysis).. CC-BY-ND 4.0 International license peer-reviewed) is the author/funder. It is made available under aThe copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/149369 doi: bioRxiv preprint first posted online Jun. 13, 2017; PURPOSE OF DATA COLLECTIONPsychiatric and learning disorders are among the most common and debilitating illnesses across the lifespan. Epidemiologic studies indicate that 75% of all diagnosable psychiatric disorders begin prior to age 241 . This underscores the need for increased focus on studies of the developing brain 2 . Beyond improving our understanding of the pathophysiology that underlies the emergence of psychiatric illness throughout development, such research has the potential to identify clinically useful markers of illness that can improve the early detection of pathology and guide interventions. Although the use of neuroimaging, neuropsychology, neurophysiology and genetics has made significant strides in revealing biological correlates for a broad array of illnesses, findings have been lacking in specificity 3 . Consequently, progress in finding clinically useful brain-based biomarkers has been disappointing 4,5 .Given the slow pace in biomarker identification, investigators have been prompted to rethink research paradigms and practices. Most notably, the emphasis on mapping diagnostic labels from a clinically defined nosology (e.g., the Diagnostic and Statistical Manual of Mental Disorders (DSM) or the International Classification of Diseases) to varying biological indices has proven to be problematic, as it assumes consistent biological relationships with broad constellations of signs and symptoms 6,7 . Epidemiologists, psychopathologists, geneticists and neuroscientists are reconsidering the relevance of diagnostic boundaries due to the lack of specif...

Background Infectious disease has a significant impact on livestock production. Availability of alternatives to antibiotics to prevent and treat disease is required to reduce reliance on antibiotics while not impacting animal welfare. Innate immune stimulants, such as mycobacterium cell wall fractions (MCWF), are used as alternatives to antibiotics for the treatment and prevention of infectious disease in a number of species including cattle, horses and dogs. This study aimed to evaluate the safety of Amplimune®, an MCWF-based immune stimulant, for weaner Angus cattle.Methods On day À1 and 0, sixty mixed-sex Angus weaner cattle were transported for 6 h before being inducted and housed in a large single pen, simulating feedlot induction conditions. The cattle were assigned to one of six treatment groups (n = 10 per group): 2 mL Amplimune intramuscularly (2IM); 2 mL Amplimune subcutaneously (2SC); 5 mL Amplimune intramuscularly (5IM); 5 mL Amplimune subcutaneously (5SC); 5 mL saline intramuscularly (SalIM) and 5 mL saline subcutaneously (SalSC) on day 0 following transportation. Body temperature, body weight, concentrations of circulating pro-inflammatory cytokines (TNFα, IL-1β, IL-6 and IL-12) and haematology parameters were measured at various times up to 96 h post-treatment. ResultsNo adverse effects from Amplimune treatment were observed. Amplimune induced an increase in circulating cytokine TNFα concentrations, total white blood cell count and lymphocyte counts indicative of activation of the innate immune system without causing an excessive inflammatory response.Conclusions Results confirm that Amplimune can be safely administered to beef cattle at the dose rates and via the routes of administration investigated here.